Prior art methods for detecting objects of interest in images are often unable to distinguish between the object of interest and its surroundings. For example, previous attempts at detecting boats in a maritime setting often fail because image intensity levels associated with the boat are often also present in the wake and/or spray created by the boat as well as the glint created by the sun reflecting off the surface of the water. Similar problems occur when trying to detect objects in an image in the presence of other environmental effects (e.g., fog, moisture in the air, smog, smoke, exhaust plumes) present in an image. Typical edge detection methods fail because edges that form on unwanted features (i.e., surroundings) are often stronger in intensity than those formed on the object of interest in the image. A need therefore exists for improved systems and methods for detecting objects in an image.